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A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables

Michael Keane () and Robert M. Sauer ()
Additional contact information
Robert M. Sauer: Bar Ilan University

No 4054, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: This paper develops a simulation estimation algorithm that is particularly useful for estimating dynamic panel data models with unobserved endogenous state variables. The new approach can easily deal with the commonly encountered and widely discussed "initial conditions problem," as well as the more general problem of missing state variables during the sample period. Repeated sampling experiments on dynamic probit models with serially correlated errors indicate that the estimator has good small sample properties. We apply the estimator to a model of married women's labor force participation decisions. The results show that the rarely used Polya model, which is very difficult to estimate given missing data problems, fits the data substantially better than the popular Markov model. The Polya model implies far less state dependence in employment status than the Markov model. It also implies that observed heterogeneity in education, young children and husband income are much more important determinants of participation, while race is much less important.

Keywords: missing data; initial conditions; female labor force participation; simulation (search for similar items in EconPapers)
JEL-codes: C15 C23 C25 J13 J21 (search for similar items in EconPapers)
Pages: 70 pages
Date: 2009-03
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Published - published in: International Economic Review, 2010, 51(4), 925-958

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https://docs.iza.org/dp4054.pdf (application/pdf)

Related works:
Journal Article: A COMPUTATIONALLY PRACTICAL SIMULATION ESTIMATION ALGORITHM FOR DYNAMIC PANEL DATA MODELS WITH UNOBSERVED ENDOGENOUS STATE VARIABLES (2010) Downloads
Working Paper: A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables (2010) Downloads
Working Paper: A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables (2004)
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